GOALI: Efficient Simulation Techniques for Comparing Constrained Systems

GOALI：用于比较约束系统的高效仿真技术

• 批准号: 0400260
• 负责人: Seong-Hee Kim
• 金额: --
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-15 至 2009-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0400260&HistoricalAwards=false
• 关键词: GOALI; Efficient; Simulation; Techniques; Comparing

This Grant Opportunity for Academic Liaison with Industry (GOALI) project is concerned with the construction of highly efficient and statistically valid procedures for comparing systems in the presence of stochastic constraints on the system behavior, assuming that both the objective and the constraints are implicit in a simulation model with few known properties. The goal is to develop statistically valid comparison procedures for solving such simulation optimization problems, and to improve the computational efficiency of the procedures to the point where they can handle up to several thousand alternatives. This involves the use of better variance estimators, common random numbers, and tighter boundaries for comparing systems. The focus of the project will be on optimization problems with discrete decision variables using fully sequential comparison procedures; this is because decision variables in industrial problems are likely to be discrete (e.g., choosing the optimal number of workers and machines) and because sequential procedures have been shown to be extremely efficient relative to other existing comparison approaches.If successful, the research will enhance the use of simulation not only as an assessment tool but also as an optimization tool. Ideally, this project would lead to the implementation of statistically valid and computationally efficient comparison procedures in simulation software; this would be achieved through close collaboration between researchers at Georgia Tech and software vendors (primarily Imagine That!). The addition of such optimization features to popular simulation software packages would be highly valuable to practitioners with respect to identifying process improvements and improved system designs in the presence of constraints about the system behavior.

这个学术与工业联络的资助机会（GOALI）项目涉及构建高效和统计有效的程序，用于在系统行为存在随机约束的情况下比较系统，假设目标和约束都隐含在具有很少已知属性的仿真模型中。目标是开发统计上有效的比较程序来解决此类模拟优化问题，并提高程序的计算效率，使其可以处理多达数千个备选方案。这涉及到使用更好的方差估计器、通用随机数和更严格的边界来比较系统。项目的重点将是离散决策变量使用全顺序比较程序的优化问题；这是因为工业问题中的决策变量可能是离散的（例如，选择工人和机器的最佳数量），并且因为顺序程序已被证明相对于其他现有的比较方法是极其有效的。如果成功，该研究将加强模拟的使用，不仅作为评估工具，而且作为优化工具。理想情况下，这个项目将导致在仿真软件中实现统计有效和计算高效的比较程序；这将通过佐治亚理工学院的研究人员和软件供应商（主要是Imagine That!）之间的密切合作来实现。将这样的优化特性添加到流行的仿真软件包中，对于在系统行为存在约束的情况下识别过程改进和改进的系统设计的实践者来说是非常有价值的。